L4L: Experience-Driven Computational Resource Control in Federated Learning

IEEE Transactions on Computers(2022)

引用 22|浏览47
暂无评分
摘要
As the large-scale deployment of machine learning applications, there is much research attention on exploiting a vast amount of data stored on mobile clients. To preserve data privacy, federated learning has been proposed to enable large-scale machine learning by massive clients without exposing raw data. Existing works of federated learning struggle for accelerating the learning process, but igno...
更多
查看译文
关键词
Collaborative work,Training,Computational modeling,Training data,Servers,Data models,Bandwidth
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要